MétaCan
Menu
Back to cohort
Record W2622453170 · doi:10.1007/s11999-017-5404-8

CORR Insights®: Reliability and Validity of the Musculoskeletal Tumor Society Scoring System for the Upper Extremity in Japanese Patients

2017· letter· en· W2622453170 on OpenAlexaffabout
Michelle Ghert

Bibliographic record

VenueClinical Orthopaedics and Related Research · 2017
Typeletter
Languageen
FieldMedicine
TopicSarcoma Diagnosis and Treatment
Canadian institutionsMcMaster UniversityHamilton Health Sciences
Fundersnot available
KeywordsScoring systemReliability (semiconductor)MedicineConsistency (knowledge bases)Quality of life (healthcare)Orthopedic surgeryCorrelationConstruct validityPhysical medicine and rehabilitationTest (biology)Physical therapyMedical physicsPsychometricsArtificial intelligenceComputer scienceSurgeryClinical psychologyMathematics

Abstract

fetched live from OpenAlex

Where Are We Now? Limb-salvage surgery for an upper or lower extremity tumor can be a life-saving procedure that allows the patient to survive with a viable and functional limb. Of course, we are left with a key question: Exactly how viable and functional are these limbs? The Musculoskeletal Tumor Society (MSTS) scoring system can help investigators and clinicians answer this question, but the MSTS score was written in English and tested on patients from the United States [7]; for it to be used elsewhere, it needs to be translated and validated in the languages spoken where the tool is used. In the current study, Uehara and colleagues psychometrically assessed the Japanese version of the MSTS scoring system for the upper extremity (MSTS-UE) and found that it had excellent test-retest reliability, acceptable internal consistency, and construct validity. In short, the MSTS-UE was consistent across time points and the domains of the scoring system, as well as measured what it was supposed to be measuring. However, the criterion validity, or the ability of the scoring system to predict another validated outcome assessed at the same time point, was found to be less consistent. Other scoring systems used to measure limb function such as the patient-derived Toronto Extremity Salvage Score (TESS) [4] showed substantial correlation. However, the correlation with the SF-36 (quality-of-life measure) physical component was fair, while correlation with the SF-36 mental component and MSTS-UE emotional acceptance component were slight to fair. The variability in scores indicates that our patients’ mental and emotional perceptions of their outcomes differ substantially from the perceptions of the physician. Where Do We Need To Go? It is apparent from the current study and one other that I know of [9] that many factors contribute to patients’ functional outcome scores following limb-salvage surgery of the upper extremity, and that physician-derived scores do not necessarily correlate with patient-reported outcomes. In some patients, quality-of-life with respect to mental and emotional health may trump domains such as ROM and strength. Given that patient-centered care should focus on patient perceptions of outcomes (as opposed to physician perception of outcomes), there remains a gap in available patient-reported outcome scores that more accurately reflect the goals of patient-centered care in oncologic limb reconstruction. One way to fill that gap is through the NIH-funded Patient Reported Outcomes Measurement Information System (PROMIS), which develops reliable and precise measures of patient-reported health status for physical, mental, and social well-being [3, 13]. This extensively validated outcomes-assessment system is available for research purposes in a wide range of health domains. PROMIS provides a timely opportunity for orthopaedic oncology specialists for validation in the oncologic limb-salvage surgery. In fact, PROMIS has been validated in patient populations with orthopaedic disorders of the upper extremity [5, 10], foot and ankle [8], and spine [2, 12] with less administrative and patient burden than other patient-reported outcomes due to the ease of online access and the user-friendly nature of the system [1]. It uses computerized adaptive testing (CAT), in which a computer algorithm customizes and selects subsequent items based on individual examinee's answers [1]. One advantage of the PROMIS system is that many of the associated measures have already been translated and validated in several other languages, and translations are in progress for many others as well [11]. Although many PROMIS items have been translated into various languages, there is an opportunity for orthopaedic oncology researchers to add to the list of translations. How Do We Get There? The full “Physical Function” PROMIS is an example of a subdomain that has yet to be translated into French, an important translation for international collaborative studies involving patients in France, Canada, and Belgium. Translators representing dialects from regions within these countries should collaborate using standardized methodology to create a universal translation that could be validated in the relevant populations. One way to do this is by applying the universal approach, meaning that one version of the translation is used for multiple countries instead of country-specific versions of the same language. Although the universal approach allows for centralized item development, and reduces bias introduced from multiple translations, it requires contributions from dialects of representative regions throughout the various countries involved. Patients with musculoskeletal tumors should be evaluated concurrently using PROMIS scores, as well as conventional assessment tools such as the MSTS and TESS. The psychometric properties of the PROMIS system in this patient population could then be evaluated. The capability of the PROMIS system to incorporate mental- and social-health domains should provide the much-needed individual patient-reported mental and emotional health domains that are missing from the MSTS and TESS. As all fields in medicine move towards a more patient-centered approach to healthcare, systems that mathematically take into account a wide variety and broach range of health domains, such as PROMIS, will help us more accurately assess patient outcomes in orthopaedic oncology. In addition, the ability to store data online and share deidentified outcomes data should provide opportunities for large-scale collaboration, not only in validation studies, but also in outcomes assessment, prospective cohort studies, and randomized trials [6].

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.101
GPT teacher head0.401
Teacher spread0.300 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueClinical Orthopaedics and Related ResearchSame topicSarcoma Diagnosis and TreatmentFrench-language works237,207